Add Perceptron binary classifier

[Th-Shivam]

Summary

Adds a binary Perceptron classifier to com.thealgorithms.machinelearning. The implementation uses deterministic zero initialization, an explicit bias term, configurable learning rate and epoch limit, input validation, single and batch prediction, defensive weight access, and convergence metadata.

Tests

• AND toy dataset converges and predicts training samples correctly.
• Unseen and batch predictions are covered.
• XOR non-separable data stops at the configured epoch limit without reporting convergence.
• Re-fitting, defensive copies, pre-fit access, invalid hyperparameters, invalid training data, and invalid prediction data are covered.

Verification

• Java 21-compatible compilation passed.
• Direct JUnit Platform execution: 11 tests passed.
• git diff --check passed.
• Full Maven/CI checks could not be run in this environment because Maven and clang-format are not installed; upstream CI should run them.

Checklist

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized it.
• All filenames are in PascalCase.
• All functions and variable names follow Java naming conventions.
• The new algorithm has a Wikipedia URL in its comments.
• The new algorithm includes a corresponding test class.
• New code follows the repository formatting style.

Closes #7599

[codecov-commenter]

Codecov Report

❌ Patch coverage is 93.75000% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 81.04%. Comparing base (1f08afb) to head (ff0842d).

Files with missing lines	Patch %	Lines
.../com/thealgorithms/machinelearning/Perceptron.java	93.75%	3 Missing and 2 partials ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##             master    #7601      +/-   ##
============================================
+ Coverage     81.01%   81.04%   +0.03%     
- Complexity     7740     7776      +36     
============================================
  Files           825      826       +1     
  Lines         24594    24674      +80     
  Branches       4810     4827      +17     
============================================
+ Hits          19925    19998      +73     
- Misses         3906     3909       +3     
- Partials        763      767       +4     

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[alxkm]

Implementation looks good overall - validation runs before any mutation in fit(), getWeights() returns a defensive copy, and there's no Random, so the tests are deterministic. I traced AND and XOR by hand and the convergence behaviour matches what the tests assert.

Two things:

1. PMD is failing the build. TooManyStaticImports allows at most 4 static imports per file. Import Assertions once and qualify the calls, as the rest of the test suite does:

import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;

-        assertArrayEquals(labels, perceptron.predict(features));
+        Assertions.assertArrayEquals(labels, perceptron.predict(features));

A wildcard static import would silence the rule but star imports are rejected too. mvn -B clean verify reproduces it locally.

2. getBias() has no positive-path coverage. It's only reached through the not-fitted path, so return bias; never executes. getWeights() is similar - the copy semantics are tested, the learned values aren't. One test covers both:

@Test
void learnsExpectedWeightsAndBias() {
    Perceptron perceptron = new Perceptron(1.0, 10);
    perceptron.fit(new double[][] {{0}, {1}}, new int[] {0, 1});

    Assertions.assertArrayEquals(new double[] {1.0}, perceptron.getWeights());
    Assertions.assertEquals(-1.0, perceptron.getBias());
}

The model converges on epoch 3 with exact values, so no delta is needed.

[alxkm]

This is what's failing the build. PMD's TooManyStaticImports allows at most 4 static imports per file; there are 5 here.

Import Assertions once and qualify the calls, as the rest of the test suite does:

Suggested change

	import static org.junit.jupiter.api.Assertions.assertArrayEquals;
	import static org.junit.jupiter.api.Assertions.assertEquals;
	import static org.junit.jupiter.api.Assertions.assertFalse;
	import static org.junit.jupiter.api.Assertions.assertThrows;
	import static org.junit.jupiter.api.Assertions.assertTrue;
	import org.junit.jupiter.api.Assertions;
	import org.junit.jupiter.api.Test;

Then update the call sites:

-        assertArrayEquals(labels, perceptron.predict(features));
-        assertTrue(perceptron.hasConverged());
+        Assertions.assertArrayEquals(labels, perceptron.predict(features));
+        Assertions.assertTrue(perceptron.hasConverged());

A wildcard static import would silence this rule but star imports are rejected too. Verify